A support vector machine (SVM) is a supervised learning model that may be used in machine learning. Typically, an SVM is associated with one or more learning processes (e.g., learning algorithms) that provide data analysis and pattern recognition. SVMs can be used, for example, in classification and regression analysis, among other tasks in statistical analysis. Binary SVMs have two statistical classes, whereas multiclass SVMs have three or more statistical classes. In any case, an SVM may be used in analyzing a given set of training examples, each such example designated as being a constituent of a given particular statistical class. From the results of its analysis, the SVM may build a model file by which new examples may be assigned into a given class.